Report Outline
Section 1: Key Findings
- Section 1A: Supporting Visualizations and Quotes
Section 2: Data Analysis Process
- Section 2A: Data Wrangling
  - Reading data with the googlesheets4 package
  - Reading gross receipts data
- Section 2B: Data Cleaning
Section 3: Data Analysis by Survey Question

Report Outline

Section 1: Key Findings
Section 1A: Supporting Visualizations and Quotes
Section 2: Data Analysis Overview
Section 2A: Data Wrangling
Section 2B: Data Cleaning
Section 3: Data Analysis by Survey Question
Section 3A: Demographic Information
Section 3B: General sentiment
Section 3C: Economic Benefit
Section 3D: Community Impact
Section 3E: Analysis on surrounding questions
Section 3F: marginal analysis on fundraising questions

Section 1: Key Findings

100% of respondents strongly agreed or agreed that the ToolBank positively impacts their CBO
100% of respondents strongly agreed or agreed that the ToolBank reduced costs related to purchasing and renting tools and equipment
86% of the survey respondents reported to at least of the minority service or leadership criteria.
Events got impacted by the TB mainly through their quality (77.8%), consistency (66.7%), and quantity (55.6%)
The most prominent types of events the toolbank supports are community building (84.4%) and service projects (75.6%)
For the past year,
half of the respondents reported that at least 1/3 (35%) of their events would have been impossible without the help of the TB
half of the respondents reported that at least 150 of their constituents (volunteers, members, and event attendees) would have been negatively impacted without the help of the TB.

Section 1A: Supporting Visualizations and Quotes

TBD

Section 2: Data Analysis Process

Section 2A: Data Wrangling

# Prompts a browser pop-up
gs4_auth()

Reading data with the googlesheets4 package

# A tibble: 6 × 27
  Timestamp           `Name of your current organization` How long have you wo…¹
  <dttm>              <chr>                               <chr>                 
1 2023-11-06 17:38:53 Baltimore ToolBank                  More than 5 years     
2 2023-11-09 12:49:19 Stillmeadow Community Projects, In… More than 5 years     
3 2023-11-09 12:49:48 Itineris Foundation Inc.            0-2 years             
4 2023-11-09 12:51:37 Friends of Fort McHenry             0-2 years             
5 2023-11-09 12:52:02 The Baltimore Station               0-2 years             
6 2023-11-09 12:55:01 MissionFit                          3-5 years             
# ℹ abbreviated name: ¹`How long have you worked with this organization?`
# ℹ 24 more variables:
#   `The following question pertains to minority leadership and service. For the purpose of this question, minority is defined as women, people of color, non-gender conforming individuals, LGBTQ+ individuals, and immigrants.\n\nWhich of the following best describes your organization?` <chr>,
#   `The ToolBank (TB) has positively impacted our Community-Based Organization (CBO) by reducing costs related to purchasing or renting tools and equipment` <chr>,
#   `The TB has positively impacted our CBO by reducing costs related to storing tools and equipment` <chr>,
#   `The TB has positively impacted our CBO by reducing staff time to complete community projects` <chr>,
#   `Tools made available through the TB allow our CBO to complete higher quality events/projects without additional funding` <chr>, …

Reading gross receipts data

# A tibble: 6 × 5
  timestamp           cbo_name                           cbo_gr cbo_size comment
  <dttm>              <chr>                              <list> <chr>    <chr>  
1 2023-11-09 12:49:19 Stillmeadow Community Projects, I… <dbl>  Small    * Cate…
2 2023-11-09 12:49:48 Itineris Foundation Inc.           <dbl>  Large    <NA>   
3 2023-11-09 12:51:37 Friends of Fort McHenry            <dbl>  Small    <NA>   
4 2023-11-09 12:52:02 The Baltimore Station              <dbl>  Medium   <NA>   
5 2023-11-09 12:55:01 MissionFit                         <dbl>  Small    <NA>   
6 2023-11-09 12:56:21 Civic Works                        <dbl>  Large    <NA>

Section 2B: Data Cleaning

Delete extra variables

# A tibble: 6 × 26
  Timestamp           `Name of your current organization` How long have you wo…¹
  <dttm>              <chr>                               <chr>                 
1 2023-11-09 12:49:19 Stillmeadow Community Projects, In… More than 5 years     
2 2023-11-09 12:49:48 Itineris Foundation Inc.            0-2 years             
3 2023-11-09 12:51:37 Friends of Fort McHenry             0-2 years             
4 2023-11-09 12:52:02 The Baltimore Station               0-2 years             
5 2023-11-09 12:55:01 MissionFit                          3-5 years             
6 2023-11-09 12:56:21 Civic Works                         3-5 years             
# ℹ abbreviated name: ¹`How long have you worked with this organization?`
# ℹ 23 more variables:
#   `The following question pertains to minority leadership and service. For the purpose of this question, minority is defined as women, people of color, non-gender conforming individuals, LGBTQ+ individuals, and immigrants.\n\nWhich of the following best describes your organization?` <chr>,
#   `The ToolBank (TB) has positively impacted our Community-Based Organization (CBO) by reducing costs related to purchasing or renting tools and equipment` <chr>,
#   `The TB has positively impacted our CBO by reducing costs related to storing tools and equipment` <chr>,
#   `The TB has positively impacted our CBO by reducing staff time to complete community projects` <chr>,
#   `Tools made available through the TB allow our CBO to complete higher quality events/projects without additional funding` <chr>, …

change column names to variables

tibble [45 × 26] (S3: tbl_df/tbl/data.frame)
 $ timestamp        : POSIXct[1:45], format: "2023-11-09 12:49:19" "2023-11-09 12:49:48" ...
 $ di_org           : chr [1:45] "Stillmeadow Community Projects, Inc." "Itineris Foundation Inc." "Friends of Fort McHenry" "The Baltimore Station" ...
 $ di_orgyearsworked: chr [1:45] "More than 5 years" "0-2 years" "0-2 years" "0-2 years" ...
 $ di_mled          : chr [1:45] "Our top executive position is held by a minority." "Our top executive position is held by a minority., More than 50% of program recipients are minorities." "None of the above" "Our top executive position is held by a minority., More than 50% of our board is made up of minorities., More t"| __truncated__ ...
 $ att_purtool      : chr [1:45] "Strongly agree" "Strongly agree" "Strongly agree" "Strongly agree" ...
 $ att_strtool      : chr [1:45] "Strongly agree" "N/A" "Agree" "Agree" ...
 $ att_redtime      : chr [1:45] "Strongly agree" "N/A" "Neutral" "Neutral" ...
 $ att_evquality    : chr [1:45] "Strongly agree" "Strongly agree" "Strongly agree" "Strongly agree" ...
 $ att_posimpact    : chr [1:45] "Strongly agree" "Strongly agree" "Strongly agree" "Strongly agree" ...
 $ att_mostimpact   : chr [1:45] "Availability of Inexpensive Rental Equipment" "You get me what I need on time and cheaply!" "Renting equipment from the TB has enabled us hold events that we wouldn't have been able to afford to do withou"| __truncated__ "The ease, availability and low cost of renting equipment through TB." ...
 $ eco_purchase     : num [1:45] 2000 200 400 5000 1000 1000 3500 2000 5000 1000 ...
 $ eco_storage      : num [1:45] 2000 0 1500 1000 0 500 1500 250 500 0 ...
 $ eco_maintain     : num [1:45] 1000 0 50 500 0 1000 250 500 200 500 ...
 $ eco_totalcost    : num [1:45] 3000 200 2800 2000 1000 5000 2000 3000 1000 0 ...
 $ eco_events       : num [1:45] 6 4 3 5 2 30 30 2 20 4 ...
 $ eco_nothost      : num [1:45] 5 0 1 0 0 10 5 0 10 4 ...
 $ eco_constit      : num [1:45] 1000 5 175 300 300 200 100 100 500 100 ...
 $ ci_exaccomp      : chr [1:45] "Hosted additional projects or events" "Hosted additional projects or events" "N/A" "More money towards other event aspects" ...
 $ ci_cutfund       : chr [1:45] "Staff" "N/A" "Projects" "Projects" ...
 $ ci_otr           : num [1:45] NA NA NA NA NA NA 5000 NA NA NA ...
 $ ci_staff         : num [1:45] 3 NA NA NA NA 0 NA NA NA NA ...
 $ ci_project       : num [1:45] NA NA 3 2 NA 8 NA 15 10 4 ...
 $ ci_evimpact      : chr [1:45] "Quantity, Quality, Consistency" "Quantity, Quality" "Quantity, Consistency" "Quality, Consistency" ...
 $ eve_type         : chr [1:45] "Service Projects, Educational Workshops, Community Building" "Fundraising, Community Building" "Fundraising, volunteer appreciation" "Fundraising, Service Projects, Community Building, Thank you Events" ...
 $ eve_fundraise    : chr [1:45] NA NA NA NA ...
 $ eve_fundraise_p  : num [1:45] 75 10 10 3 2 30 25 0 50 0 ...

change multiple choice answer into numbers

# A tibble: 6 × 26
  timestamp           di_org   di_orgyearsworked di_mled att_purtool att_strtool
  <dttm>              <chr>                <dbl> <chr>   <chr>       <chr>      
1 2023-11-09 12:49:19 Stillme…                 3 Our to… Strongly a… Strongly a…
2 2023-11-09 12:49:48 Itineri…                 1 Our to… Strongly a… N/A        
3 2023-11-09 12:51:37 Friends…                 1 None o… Strongly a… Agree      
4 2023-11-09 12:52:02 The Bal…                 1 Our to… Strongly a… Agree      
5 2023-11-09 12:55:01 Mission…                 2 Our to… Strongly a… Neutral    
6 2023-11-09 12:56:21 Civic W…                 2 More t… Strongly a… Strongly a…
# ℹ 20 more variables: att_redtime <chr>, att_evquality <chr>,
#   att_posimpact <chr>, att_mostimpact <chr>, eco_purchase <dbl>,
#   eco_storage <dbl>, eco_maintain <dbl>, eco_totalcost <dbl>,
#   eco_events <dbl>, eco_nothost <dbl>, eco_constit <dbl>, ci_exaccomp <chr>,
#   ci_cutfund <chr>, ci_otr <dbl>, ci_staff <dbl>, ci_project <dbl>,
#   ci_evimpact <chr>, eve_type <chr>, eve_fundraise <chr>,
#   eve_fundraise_p <dbl>

The following section is commented out as we used text format choices in the following study

split check all that apply responses into indicators

# A tibble: 6 × 30
  timestamp           di_org   di_orgyearsworked di_mled att_purtool att_strtool
  <dttm>              <chr>                <dbl> <chr>   <chr>       <chr>      
1 2023-11-09 12:49:19 Stillme…                 3 Our to… Strongly a… Strongly a…
2 2023-11-09 12:49:48 Itineri…                 1 Our to… Strongly a… N/A        
3 2023-11-09 12:51:37 Friends…                 1 None o… Strongly a… Agree      
4 2023-11-09 12:52:02 The Bal…                 1 Our to… Strongly a… Agree      
5 2023-11-09 12:55:01 Mission…                 2 Our to… Strongly a… Neutral    
6 2023-11-09 12:56:21 Civic W…                 2 More t… Strongly a… Strongly a…
# ℹ 24 more variables: att_redtime <chr>, att_evquality <chr>,
#   att_posimpact <chr>, att_mostimpact <chr>, eco_purchase <dbl>,
#   eco_storage <dbl>, eco_maintain <dbl>, eco_totalcost <dbl>,
#   eco_events <dbl>, eco_nothost <dbl>, eco_constit <dbl>, ci_exaccomp <chr>,
#   ci_cutfund <chr>, ci_otr <dbl>, ci_staff <dbl>, ci_project <dbl>,
#   ci_evimpact <chr>, eve_type <chr>, eve_fundraise <chr>,
#   eve_fundraise_p <dbl>, di_mled_top <dbl>, di_mled_board <dbl>, …

[1] 4
[1] 5
[1] 7
[1] 8
[1] 13
[1] 15
[1] 18
[1] 22
[1] 27
[1] 30
[1] 37

# A tibble: 6 × 34
  timestamp           di_org   di_orgyearsworked di_mled att_purtool att_strtool
  <dttm>              <chr>                <dbl> <chr>   <chr>       <chr>      
1 2023-11-09 12:49:19 Stillme…                 3 Our to… Strongly a… Strongly a…
2 2023-11-09 12:49:48 Itineri…                 1 Our to… Strongly a… N/A        
3 2023-11-09 12:51:37 Friends…                 1 None o… Strongly a… Agree      
4 2023-11-09 12:52:02 The Bal…                 1 Our to… Strongly a… Agree      
5 2023-11-09 12:55:01 Mission…                 2 Our to… Strongly a… Neutral    
6 2023-11-09 12:56:21 Civic W…                 2 More t… Strongly a… Strongly a…
# ℹ 28 more variables: att_redtime <chr>, att_evquality <chr>,
#   att_posimpact <chr>, att_mostimpact <chr>, eco_purchase <dbl>,
#   eco_storage <dbl>, eco_maintain <dbl>, eco_totalcost <dbl>,
#   eco_events <dbl>, eco_nothost <dbl>, eco_constit <dbl>, ci_exaccomp <chr>,
#   ci_cutfund <chr>, ci_otr <dbl>, ci_staff <dbl>, ci_project <dbl>,
#   ci_evimpact <chr>, eve_type <chr>, eve_fundraise <chr>,
#   eve_fundraise_p <dbl>, di_mled_top <dbl>, di_mled_board <dbl>, …

[1] 7
[1] 12
[1] 13
[1] 15
[1] 21
[1] 22
[1] 27

# A tibble: 6 × 38
  timestamp           di_org   di_orgyearsworked di_mled att_purtool att_strtool
  <dttm>              <chr>                <dbl> <chr>   <chr>       <chr>      
1 2023-11-09 12:49:19 Stillme…                 3 Our to… Strongly a… Strongly a…
2 2023-11-09 12:49:48 Itineri…                 1 Our to… Strongly a… N/A        
3 2023-11-09 12:51:37 Friends…                 1 None o… Strongly a… Agree      
4 2023-11-09 12:52:02 The Bal…                 1 Our to… Strongly a… Agree      
5 2023-11-09 12:55:01 Mission…                 2 Our to… Strongly a… Neutral    
6 2023-11-09 12:56:21 Civic W…                 2 More t… Strongly a… Strongly a…
# ℹ 32 more variables: att_redtime <chr>, att_evquality <chr>,
#   att_posimpact <chr>, att_mostimpact <chr>, eco_purchase <dbl>,
#   eco_storage <dbl>, eco_maintain <dbl>, eco_totalcost <dbl>,
#   eco_events <dbl>, eco_nothost <dbl>, eco_constit <dbl>, ci_exaccomp <chr>,
#   ci_cutfund <chr>, ci_otr <dbl>, ci_staff <dbl>, ci_project <dbl>,
#   ci_evimpact <chr>, eve_type <chr>, eve_fundraise <chr>,
#   eve_fundraise_p <dbl>, di_mled_top <dbl>, di_mled_board <dbl>, …

[1] 15
[1] 29

# A tibble: 6 × 43
  timestamp           di_org   di_orgyearsworked di_mled att_purtool att_strtool
  <dttm>              <chr>                <dbl> <chr>   <chr>       <chr>      
1 2023-11-09 12:49:19 Stillme…                 3 Our to… Strongly a… Strongly a…
2 2023-11-09 12:49:48 Itineri…                 1 Our to… Strongly a… N/A        
3 2023-11-09 12:51:37 Friends…                 1 None o… Strongly a… Agree      
4 2023-11-09 12:52:02 The Bal…                 1 Our to… Strongly a… Agree      
5 2023-11-09 12:55:01 Mission…                 2 Our to… Strongly a… Neutral    
6 2023-11-09 12:56:21 Civic W…                 2 More t… Strongly a… Strongly a…
# ℹ 37 more variables: att_redtime <chr>, att_evquality <chr>,
#   att_posimpact <chr>, att_mostimpact <chr>, eco_purchase <dbl>,
#   eco_storage <dbl>, eco_maintain <dbl>, eco_totalcost <dbl>,
#   eco_events <dbl>, eco_nothost <dbl>, eco_constit <dbl>, ci_exaccomp <chr>,
#   ci_cutfund <chr>, ci_otr <dbl>, ci_staff <dbl>, ci_project <dbl>,
#   ci_evimpact <chr>, eve_type <chr>, eve_fundraise <chr>,
#   eve_fundraise_p <dbl>, di_mled_top <dbl>, di_mled_board <dbl>, …

[1] 3
[1] 4
[1] 7
[1] 13
[1] 27
[1] 42

# A tibble: 6 × 48
  timestamp           di_org   di_orgyearsworked di_mled att_purtool att_strtool
  <dttm>              <chr>                <dbl> <chr>   <chr>       <chr>      
1 2023-11-09 12:49:19 Stillme…                 3 Our to… Strongly a… Strongly a…
2 2023-11-09 12:49:48 Itineri…                 1 Our to… Strongly a… N/A        
3 2023-11-09 12:51:37 Friends…                 1 None o… Strongly a… Agree      
4 2023-11-09 12:52:02 The Bal…                 1 Our to… Strongly a… Agree      
5 2023-11-09 12:55:01 Mission…                 2 Our to… Strongly a… Neutral    
6 2023-11-09 12:56:21 Civic W…                 2 More t… Strongly a… Strongly a…
# ℹ 42 more variables: att_redtime <chr>, att_evquality <chr>,
#   att_posimpact <chr>, att_mostimpact <chr>, eco_purchase <dbl>,
#   eco_storage <dbl>, eco_maintain <dbl>, eco_totalcost <dbl>,
#   eco_events <dbl>, eco_nothost <dbl>, eco_constit <dbl>, ci_exaccomp <chr>,
#   ci_cutfund <chr>, ci_otr <dbl>, ci_staff <dbl>, ci_project <dbl>,
#   ci_evimpact <chr>, eve_type <chr>, eve_fundraise <chr>,
#   eve_fundraise_p <dbl>, di_mled_top <dbl>, di_mled_board <dbl>, …

Merge Gross Recipts to datasheet and add stratification

# A tibble: 6 × 51
  timestamp           di_org   di_orgyearsworked di_mled att_purtool att_strtool
  <dttm>              <chr>                <dbl> <chr>   <chr>       <chr>      
1 2023-11-09 12:49:19 Stillme…                 3 Our to… Strongly a… Strongly a…
2 2023-11-09 12:49:48 Itineri…                 1 Our to… Strongly a… N/A        
3 2023-11-09 12:51:37 Friends…                 1 None o… Strongly a… Agree      
4 2023-11-09 12:52:02 The Bal…                 1 Our to… Strongly a… Agree      
5 2023-11-09 12:55:01 Mission…                 2 Our to… Strongly a… Neutral    
6 2023-11-09 12:56:21 Civic W…                 2 More t… Strongly a… Strongly a…
# ℹ 45 more variables: att_redtime <chr>, att_evquality <chr>,
#   att_posimpact <chr>, att_mostimpact <chr>, eco_purchase <dbl>,
#   eco_storage <dbl>, eco_maintain <dbl>, eco_totalcost <dbl>,
#   eco_events <dbl>, eco_nothost <dbl>, eco_constit <dbl>, ci_exaccomp <chr>,
#   ci_cutfund <chr>, ci_otr <dbl>, ci_staff <dbl>, ci_project <dbl>,
#   ci_evimpact <chr>, eve_type <chr>, eve_fundraise <chr>,
#   eve_fundraise_p <dbl>, di_mled_top <dbl>, di_mled_board <dbl>, …

Section 3: Data Analysis by Survey Question

Section 3A: Demographic Information

Question: How long have you worked with this organization?


 1  2  3 
11 15 19

               time RespondentCount Percentage
1         0-2 years              11      0.244
2         3-5 years              15      0.333
3 More than 5 years              19      0.422

[1] 4.111111

[1] 1.991142

[1] 4

Question 3: The following question pertains to minority leadership and service. For the purpose of this question, minority is defined as women, people of color, and immigrants. Ehich of the following best describes your organization? (please provide your best estimate).?

Percent of respondents stating, “our top executive position is held by a minority”

  count.Var1 count.Freq Percentage.Var1 Percentage.Freq
1          0         20               0       0.4444444
2          1         25               1       0.5555556

Percent of respondents stating, “More than 50% of our board is made up of minorities”

  count.Var1 count.Freq Percentage.Var1 Percentage.Freq
1          0         26               0       0.5777778
2          1         19               1       0.4222222

Percent of respondents stating, “More than 50% of program recipients are minorities”

  count.Var1 count.Freq Percentage.Var1 Percentage.Freq
1          0         19               0       0.4222222
2          1         26               1       0.5777778

Percent of respondents stating, “None of the above”

  count.Var1 count.Freq Percentage.Var1 Percentage.Freq
1          0         40               0       0.8888889
2          1          5               1       0.1111111

Based on the metrics above, 86% of the survey respondents reported to at least of the minority service or leadership criteria.

Section 3B: General sentiment

Questions 4-8:Plots of General sentiment and Years with the CBO

Questions 4-8: Plots of General sentiment and size of CBO

	Number Respondants	Percent of Total Respondants
Number, percentages of CBOs in size categories
CBO Size
Less than 500k (group 1)	29	64.4%
Between 500k and 1000k (group 2)	3	6.7%
Greater than 1000k (group 3)	13	28.9%
NA	0	0%

Questions 4-8: Plots of General Sentiment and Minority Status

	# Yes (% Yes)	# No (% No)
Number, percentages of respondants indicating minority leadership
Minority Leadership
Our top executive position is held by a minority	25 (56%)	20 (44%)
More than 50% of our board is made up of minorities	19 (42%)	26 (58%)
More than 50% of program recipients are minorities	26 (58%)	19 (42%)
None of the above	5 (11%)	40 (89%)

Response analysis

overall table:

	#Strongly Agree (%)	#Agree (%)	#Neutral (%)	#Disagree (%)	#Strongly Disagree (%)	#N/A (%)
Number, percentages of respondants to sentiment questions
TB has pos. impacted our CBO by reducing costs related to purchasing or renting tools and equipment	42 (93.3%)	3 (6.7%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)
TB has pos. impacted our CBO by reducing costs related to storing tools and equipment	26 (57.8%)	7 (15.6%)	7 (15.6%)	0 (0%)	0 (0%)	5 (11.1%)
TB has pos. impacted our CBO by reducing staff time to complete maintenance/projects	19 (42.2%)	11 (24.4%)	8 (17.8%)	2 (4.4%)	0 (0%)	5 (11.1%)
the Tools made available through the TB allow our CBO to complete higher quality events/projects without additional funding	36 (80%)	7 (15.6%)	2 (4.4%)	0 (0%)	0 (0%)	0 (0%)
TB has pos. impacted our CBO	42 (93.3%)	3 (6.7%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)

Percent of respondents that reported “Agreeing” or “Strongly Agreeing” that, “the ToolBank (TB) has positively impacted our CBO by reducing costs related to purchasing or renting tools and equipment”

      count.Var1 count.Freq Percentage.Var1 Percentage.Freq
1          Agree          3           Agree      0.06666667
2 Strongly agree         42  Strongly agree      0.93333333

Percent of respondents that reported “Agreeing” or “strongly Agreeing” that, “the TB has positively impacted our CBO by reducing costs related to storing tools and equipment

      count.Var1 count.Freq Percentage.Var1 Percentage.Freq
1          Agree          7           Agree       0.1555556
2            N/A          5             N/A       0.1111111
3        Neutral          7         Neutral       0.1555556
4 Strongly agree         26  Strongly agree       0.5777778

Percent of respondents that reported “Agreeing” or “strongly Agreeing” that, “the TB has positively impacted our CBO by reducing staff time to complete maintenance/projects

      count.Var1 count.Freq Percentage.Var1 Percentage.Freq
1          Agree         11           Agree      0.24444444
2       Disagree          2        Disagree      0.04444444
3            N/A          5             N/A      0.11111111
4        Neutral          8         Neutral      0.17777778
5 Strongly agree         19  Strongly agree      0.42222222

Percent of respondents that reported “Agreeing” or “strongly Agreeing” that, “the Tools made available through the TB allow our CBO to complete higher quality events/projects without additional funding

      count.Var1 count.Freq Percentage.Var1 Percentage.Freq
1          Agree          7           Agree      0.15555556
2        Neutral          2         Neutral      0.04444444
3 Strongly agree         36  Strongly agree      0.80000000

Question: TB has positively impacted our CBO

      count.Var1 count.Freq Percentage.Var1 Percentage.Freq
1          Agree          3           Agree      0.06666667
2 Strongly agree         42  Strongly agree      0.93333333

Plots

Section 3C: Economic Benefit

Response analysis

Question: How much would you have spent purchasing or renting tools and equipment had the TB not existed?

       Measure     Value
1         Mean  5028.889
2       Median  2000.000
3         Mode  2000.000
4           sd 14108.953
5 1st quantile   500.000
6 3rd quantile  3500.000

Question: How much would you have spent on storage of tools and equipment had the TB not existed ?

       Measure     Value
1         Mean  925.5556
2       Median  500.0000
3         Mode    0.0000
4           sd 1195.7606
5 1st quantile    0.0000
6 3rd quantile 1200.0000

Question: How much would you have spent on maintenance of tools and equipment had the TB not existed?

       Measure     Value
1         Mean  816.6667
2       Median  300.0000
3         Mode  500.0000
4           sd 2227.4466
5 1st quantile   80.0000
6 3rd quantile  500.0000

Question: Reflecting on your events in the past year: If the TB did not exist, how much funding would your organization allocate to buying, storing, tracking and maintaining your own inventory of tools and equipment?

       Measure    Value
1         Mean 2527.111
2       Median 1500.000
3         Mode 5000.000
4           sd 2532.100
5 1st quantile  800.000
6 3rd quantile 3000.000

Question: number of total events hosted during last year

       Measure    Value
1         Mean 17.55556
2       Median  6.00000
3         Mode  3.00000
4           sd 25.65466
5 1st quantile  4.00000
6 3rd quantile 20.00000

Question: If there were no TB, how many of your events in the past year would you not have been hosted for any reason?

       Measure     Value
1         Mean  6.222222
2       Median  2.000000
3         Mode  0.000000
4           sd 15.597041
5 1st quantile  1.000000
6 3rd quantile  5.000000

Extra analysis: percent of event not host during last year

  Measure     Value
1    Mean 0.4057342
2  Median 0.3500000
3    Mode 0.0000000

Questions: If there were no TB, how many of your constituents, including volunteers, members, and event attendees, would have been negatively impacted in the past year?

       Measure    Value
1         Mean 1306.444
2       Median  150.000
3         Mode  100.000
4           sd 3077.895
5 1st quantile   75.000
6 3rd quantile  500.000

Calculated:

Reflecting on your events in the past year, how many events did your organization host?

If there were no TB, how many of your events in the past year would you not have been able to host?

What percentage of the events hosted last year did the TB help make possible?

put all this into one table:

	Mean	25th quantile	Median	Mode	75th quantile	Standard deviation
Impact on CBO if TB did not exists
Money That Would Have Been Spent if TB Did Not Exist*
on Purchasing or renting tools and equipment	5029	500	2000	2000	3500	14109
on storage of tools and equipment	926	0	500	0	1200	1196
on maintenance of tools and equipment	817	80	300	500	500	2227
on buying, storing, tracking and maintaining own tool+equiptment inventory	2527	800	1500	5000	3000	2532
# Events/People Impacted If TB Did Not Exist
# events that would have been impossible in past year	6	1	2	0	5	16
% of CBO’s total events that would have been impossible in past year	41	4	35	0	62	36
# constituents that would have been negatively impacted in the past year	1306	75	150	100	500	3078
*in US dollars

Plots

# A tibble: 1 × 1
  `Average % of a CBO's events possible through TB in past year`
                                                           <dbl>
1                                                           40.6

Section 3D: Community Impact

Question: With the money that you have saved on purchasing, storing, and maintaining tools and equipment, what have you been able to accomplish?

                               choices frequency percentage
1     Hired additional staff positions         2      0.044
2 Hosted additional projects or events        27        0.6
3                                other        11      0.244

Question: Without the TB, what would you no longer be able to fund?

   choices frequency percentage
1    Staff         2      0.044
2 Projects        26      0.578
3    other         7      0.156

Among partners indicated certain effect, what is the average quantified effects

[1] 1.5

[1] 2.12132

[1] 5.04

[1] 4.568734

	# Respondants	% Respondants
Number, percentages of where Respondants report funding
Accomplishments through money saved through TB
Hired more staff	2	4.4%
Hosted additional projects/events	27	60%
Other	11	24.4%
Where funding would be cut if TB did not exist
Cut staff funding	2	4.4%
Cut project funding	26	57.8%
Other	7	15.6%

Quantify effect of “other”, if selected

Section 3E: Analysis surrounding questions

Question: do organizations with higher savings through toolbank report more of a positive impact?

Question: How do savings vary by different toolbank offerings?

Question: What is the relationship like between minority-led CBOs and the toolbank compared to non-minority led CBOs?

Question: where within the organization does the Toolbank impact most?

Histogram, faceted by responded staff versus responded projects– can incorporate “Other” if consistent across organizations X = number (of staff or projects) Facet: Without the TB, what would you no longer be able to fund? (code note: will also have to manipulate data a bit to get this)

Question: In what ways has the community benefited through the toolbank? What are the most prominent types of events (or organization types) the toolbank supports?

2 bar chart X1 = ways of impact; X2 = event types Y = % respondent Can incorporate other if there is consistency across respondents

      choices frequency percentage
1    Quantity        25      0.556
2     Quality        35      0.778
3   Diversity         8      0.178
4 Consistency        30      0.667
5       other         2      0.044

                choices frequency percentage
1           Fundraising        14      0.311
2      Service Projects        34      0.756
3 Educational Workshops        15      0.333
4    Community Building        38      0.844
5                 other         6      0.133

Section 3F: marginal analysis on fundraising questions

[1] 45

[1] 32.82222

[1] 30

[1] 28.83124

  0%  25%  50%  75% 100% 
   0   10   30   50  100

Baltimore Community Data Science Collaboration, ToolBank Community and Economic Impact Survey Analysis

Analysis by: Charlotte Clapham, Tianxu Chen, Haley Farrie

2023-11-23

Report Outline

Section 1: Key Findings

Section 1A: Supporting Visualizations and Quotes

Section 2: Data Analysis Process

Section 2A: Data Wrangling

Reading data with the googlesheets4 package

Reading gross receipts data

Section 2B: Data Cleaning

Delete extra variables

change column names to variables

change multiple choice answer into numbers

split check all that apply responses into indicators

Merge Gross Recipts to datasheet and add stratification

Section 3: Data Analysis by Survey Question

Section 3A: Demographic Information

Question: How long have you worked with this organization?

Question 3: The following question pertains to minority leadership and service. For the purpose of this question, minority is defined as women, people of color, and immigrants. Ehich of the following best describes your organization? (please provide your best estimate).?

Section 3B: General sentiment

Questions 4-8:Plots of General sentiment and Years with the CBO

Questions 4-8: Plots of General sentiment and size of CBO

Questions 4-8: Plots of General Sentiment and Minority Status

Response analysis

Plots

Section 3C: Economic Benefit

Response analysis

Plots

Section 3D: Community Impact

Section 3E: Analysis surrounding questions

Section 3F: marginal analysis on fundraising questions